advances in the analysis of complex food matrices: species identification in surimi...
TRANSCRIPT
RESEARCH ARTICLE
Advances in the analysis of complex food
matrices: Species identification in surimi-
based products using Next Generation
Sequencing technologies
Alice Giusti1☯, Andrea Armani1☯*, Carmen G. Sotelo2*
1 FishLab, Department of Veterinary Sciences, University of Pisa, Pisa, Italy, 2 Instituto de Investigaciones
Marinas (IIM-CSIC), Vigo, Spain
☯ These authors contributed equally to this work.
* [email protected] (AA); [email protected] (CGS)
Abstract
The Next Generation Sequencing (NGS) technologies represent a turning point in the food
inspection field, particularly for species identification in matrices composed of a blend of two
or more species. In this study NGS technologies were applied by testing the usefulness of
the Ion Torrent Personal Genome Machine (PGM) in seafood traceability. Sixteen commer-
cial surimi samples produced both in EU and non-EU countries were analysed. Libraries
were prepared using a universal primer pair able to amplify a short 16SrRNA fragment from
a wide range of fish and cephalopod species. The mislabelling rate of the samples was also
evaluated. Overall, DNA from 13 families, 19 genera and 16 species of fish, and from 3 fami-
lies, 3 genera and 3 species of cephalopods was found with the analysis. Samples produced
in non-EU countries exhibited a higher variability in their composition. 37.5% of the surimi
products were found to be mislabelled. Among them, 25% voluntary declared a species dif-
ferent from those identified and 25% (all produced in non-EU countries) did not report the
presence of molluscs on the label, posing a potential health threat for allergic consumers.
The use of vulnerable species was also proved. Although the protocol should be further opti-
mized, PGM platform proved to be a useful tool for the analysis of complex, highly pro-
cessed products.
Introduction
Present changes in socio-demographic features and people lifestyle, particularly in devel-
oped countries, have radically shifted consumers’ eating habits and their market choices.
With the general increasingly speeding lifestyles and individualisation tendencies, available
time for cooking has in fact reduced, so consumers normally prefer “time saving” products
as well as affordable prices. Ready-to-eat products, which do not require a further heating or
processing step before consumption, have increasingly appeal consents due to their cheap-
ness, storage easiness and attractive appearance [1]. Among products of animal origin, many
PLOS ONE | https://doi.org/10.1371/journal.pone.0185586 October 2, 2017 1 / 18
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OPENACCESS
Citation: Giusti A, Armani A, Sotelo CG (2017)
Advances in the analysis of complex food matrices:
Species identification in surimi-based products
using Next Generation Sequencing technologies.
PLoS ONE 12(10): e0185586. https://doi.org/
10.1371/journal.pone.0185586
Editor: Massimo Labra, Universita degli Studi di
Milano-Bicocca, ITALY
Received: June 14, 2017
Accepted: September 17, 2017
Published: October 2, 2017
Copyright: © 2017 Giusti et al. This is an open
access article distributed under the terms of the
Creative Commons Attribution License, which
permits unrestricted use, distribution, and
reproduction in any medium, provided the original
author and source are credited.
Data Availability Statement: All relevant data are
within the paper.
Funding: LABELFISH. ATLANTIC NETWORK ON
GENETIC CONTROL OF FISH AND SEAFOOD
LABELLING AND TRACEABILITY, funded by
Atlantic Area Programme (INTERREG IVB) 2011-1/
163 REF 1070134; URL: http://www.atlanticarea.
eu/. The funders had no role in study design, data
collection and analysis, decision to publish, or
preparation of the manuscript.
processed foods can be included under the definition of ready-to-eat food, such as ham, sau-
sages, dairy products (milk, cheese, spreads), smoked fish, prepared salads, nuggets and
others.
Surimi is a stabilized myofibrillar protein compound obtained from mechanically deboned
fish flesh that is repeatedly washed with water and blended with cryoprotectants [2]. This fish
paste represents an intermediate product used in the preparation of a variety of ready-to-eat
seafood commodities, called surimi-based products (SBPs), marketed in different forms such
as sticks, slices, crumbs, lobster tails-like, etc. [3]. SBPs, originally produced, marketed and
consumed in Asian countries, are increasingly appreciated worldwide, especially in North
America and Europe [4]. To date, they are in fact commonly produced also by Western food
processing industries. Initially, Alaska pollock (Gadus chalcogrammus) was the main species
used for surimi production. Then, due to its overexploitation, numerous previously underuti-
lized fish species have started to be used [2, 5–7]. Cephalopods, particularly squids, are also
often used in surimi manufacture [2,4], mainly thanks to the gelation properties of their pro-
teins or as flavouring ingredients [8]. Therefore, surimi represents a multispecies seafood
product, as its production can imply the use of an extremely wide range of species [2,5].
According to the current EU law on food labelling, it is not mandatory to provide the commer-
cial and/or scientific name of the seafood species present in SBPs [9–11], although some
brands report it voluntarily (author’s note). However, the presence of ingredients potentially
causing allergies, listed in the Regulation (EU) No 1169/2011 (including “fish” and “molluscs”)
must be declared. As they never represent the major ingredient of SBPs, the use of cephalopods
may be undeclared, causing a potential hazard for allergic consumers.
Since surimi is a highly processed product, the use of morphological characters to identify
which species have been used is impossible. Thus, species identification through DNA analy-
sis is useful to verify the information reported on the label (if the species is declared) and to
detect the eventual presence of undeclared allergenic ingredients such as cephalopods. More-
over, it allows to promote the sustainable environmental management, particularly if overex-
ploited and/or endangered fish species are used. SBPs were actually proved to be particularly
involved in mislabelling cases, regardless of their origin [5–7]. However, few studies assessing
the composition of these types of products have been conducted since now, as the possibility
to detect species within products containing a mixture of species goes beyond the capability
of the analytical techniques routinely applied in food control. Available studies applied
DNA-based techniques involving a classical Sanger-based DNA sequencing phase, such as
FINS [7] as well as DNA-Barcoding [6]. However, Sanger-based DNA sequencing alone has
often been considered a not feasible approach for a complete description of species composi-
tion in mixed food analysis. Galal-Khallaf et al. [5] have recently highlighted the necessity to
appeal to more suitable techniques for these products, combining the classical direct
sequencing of PCR products with a PCR cloning technique with subsequent plasmid
sequencing. PCR cloning, even though effective, is a rather laborious and time-consuming
approach to be routinely used in laboratories. In this regard, a metagenomics approach,
using High Throughput Sequencing technologies, commonly known as Next Generation
Sequencing (NGS), represents a useful alternative to PCR cloning to identify species in highly
processed multispecies products. This technique is faster and even more informative than
cloning, since it can detect also low-represented species in mixtures [12]. Because of that,
NGS results attractive for food inspection research field, even though they cannot yet be con-
sidered enough mature to be applied as routine method. More studies aimed at improving its
accuracy as well as correcting their error sources are needed [13]. Preliminary studies were
performed on artificial mixtures of meat species to verify the method’s robustness [14,15]
and the NGS have been practically applied to commercial products in the work of Muñoz-
Species identification in surimi-based products using Next Generation Sequencing technologies
PLOS ONE | https://doi.org/10.1371/journal.pone.0185586 October 2, 2017 2 / 18
Competing interests: The authors have declared
that no competing interests exist.
Colmenero et al. [16], that detected the animal species contained in candies, that were
selected as a model of highly processed foods. As regards seafood, to the best of our knowl-
edge, NGS technologies have been applied in commercial fish cakes [17], as well as in highly
processed cod products [18]. In addition, Kappel et al. [19] tested their effectiveness in dis-
criminating tuna species within experimental mixtures. Given the scarce available literature,
more studies focused in optimizing NGS protocols and testing the potentiality of these tech-
nologies in seafood analysis are undoubtedly required. In fact, although the still quite high
costs, NGS prices are progressively dropping during the years, so that, in a near future, these
techniques could be routinely applied to this research field.
A preliminary study, conducted with the aim to help in the preparation phase of NGS
libraries, showed the ability of the primer’s pair developed by Chapela et al. [20] to amplify a
short fragment of mitochondrial 16S ribosomal gene (16SrRNA) in many fish and cephalopod
species used in surimi production [21]. In the present study, we used for the first time the Ion
Torrent Personal Genome Machine (PGM) to apply a metabarcoding approach to the analysis
of the composition of some surimi-based products (SBPs) purchased on international market.
The primer’s pair of Chapela et al. [20] was used for amplifying the DNA fragment to be
turned into standard libraries. This study aimed at providing an analytical starting point to
better approach such new techniques for their future application to a wider range of multispe-
cies seafood products.
Materials and methods
Samples collection and DNA extraction
Sixteen SBPs were collected (Table 1). Among them, fourteen were purchased from Spanish
and Italian grocery stores and two were collected from imports coming from third countries
by the staff of the Border Inspection Post (BIP) of Leghorn (Italy). All the samples were stored
at -20˚C before DNA extraction. Total DNA was extracted from all the SBPs with the protocol
proposed by Armani et al. [22], starting from 100 mg of tissue, and quantified using a Qubit™3.0 Fluorometer (Thermo Fisher Scientific).
DNA amplification and purification
The DNA samples were amplified with the primer pairs 16sf-var 5´-CAAATTACGCTGTTATCCCTATGG-3´ and 16sr-var 5´-GACGAGAAGACCCTAATGAGCTTT-3´designed by Cha-
pela et al. [20] using illustra™ puReTaq Ready-To-Go™ PCR Beads (GE Healthcare). For each
tube containing the bead, 2 μl of 200 nM of each primer, 1 μl of 50 ng of template DNA and
nuclease-free water (Life Technologies) were added, for a final reaction volume of 25 μl. DNA
was amplified on an Applied Biosystems Veriti™ 96 well Thermal Cycler (Thermo Fisher Scien-
tific) with the following cycling program: denaturation at 94˚C for 3 min; 35 cycles at 94˚C for
40 s, 60˚C for 40 s, and 72˚C for 40 s; final extension at 72˚C for 7 min. 5 μL of each PCR prod-
uct was checked by electrophoresis on a 2% agarose gel and the presence of fragments of the
expected length was assessed by a comparison with the standard marker O’GeneRuler DNA
Ladder (Thermo Fisher Scientific). Double-stranded PCR products were purified with Agen-
court1 AMPure1 XP Kit for DNA purification (Beckman Coulter, Beverly, Massachusetts,
USA) on a DynaMag™-2 magnet magnetic rack (Thermo Fisher Scientific) following the proce-
dure proposed by the manufacturer. Purified PCR products were quantified using a Qubit™ 3.0
Fluorometer (Thermo Fisher Scientific).
Species identification in surimi-based products using Next Generation Sequencing technologies
PLOS ONE | https://doi.org/10.1371/journal.pone.0185586 October 2, 2017 3 / 18
Table 1. Commercial SBPs analysed in this study.
Sample
(IC)
Collection
site
Producer
country
Commercial denomination/
product description
Ingredients Declared species
SUR-1 Big
distribution
(Spain)
Spain Surimi product—Sticks Surimi (fish), water, sunflower oil, cephalopod (mollusc), starch and modified
starch, salt, egg albumin, vegetable protein, flavor (containing shellfish), flavor
enhancer (monosodium glutamate), sugar, natural dyes (cochineal and
paprika extract)
ND
SUR-2 Big
distribution
(Spain)
Germany Cooled surimi product Surimi (Fish), water, cephalopod (mollusc), sunflower oil, starch modified,
wheat flour, soy protein, sea salt, vegetable protein, egg albumen, flavor
(contains crustaceans) and cephalopod ink (mollusc)
ND
SUR-3 Big
distribution
(Spain)
Spain Grated surimi product Surimi (fish), water, sunflower oil, cephalopod (mollusc), starch and modified
starch, salt, egg albumin, vegetable protein, flavor (containing crustacea),
flavor enhancer (monosodium glutamate), sugar, natural colorings (cochineal
and paprika extract)
ND
SUR-4 Big
distribution
(Spain)
Spain Sticks Surimi 47% [fish and cephalopods (molluscs)], water, corn starch, modified
starches (gluten), sunflower oil, aroma and crab extract [crustaceans, soy
flavor enhancer (monosodium glutamate, E635)], salt, egg, vegetable protein
(gluten), coloring (paprika extract)
ND
SUR-5 Big
distribution
(Spain)
Spain Surimi slices Surimi 49% (fish), water, rice starch, sunflower oil, crab aroma and extract
[crustaceans, molluscs, soy flavor enhancers (monosodium glutamate, E
635)], egg albumin, protein vegetable (gluten), modified starch (gluten), salt,
sugar, preservative (potassium sorbate, coloring (paprika extract)
ND
SUR-6 Big
distribution
(Spain)
France Surimi duo–lobster flavour 38% Surimi (Fish pulp 92% -Micromesistius poutassou, sugar, trehalose,
stabilizers: sorbitols, E450, E451), water, wheat starch (contains gluten),
rehydrated egg powder, canola oil, salt, flavorings (contains gluten, fish and
shellfish), sugar, flavor enhancer: monosodium glutamate; coloring: paprika
extract
Micromesistius
poutassou
SUR-7 Big
distribution
(Spain)
Spain Surimi sticks–seafood
flavour
Surimi (Fish), water, starch and modified starch, cephalopod (mollusc),
sunflower oil, egg whites, vegetable protein, salt, flavor enhancer (E621),
flavor (contains crustaceans), sugar, coloring (E120 and E160c)
ND
SUR-8 Big
distribution
(Spain)
Spain Surimi sticks Surimi (Fish), water, sunflower oil, cephalopod (mollusc), starch and modified
starch, crab extracto (crustacean), salt, egg whites, vegetable protein, flavor
enhancer (monosodium glutamate), white wine extract, sugar, natural
colorings (cochineal and paprika extract)
ND
SUR-9 Big
distribution
(Spain)
Spain Processed seafood product
with garlic
Fish protein, water, sunflower oil, wheat flour, cephalopod (mollusc), olive
oil, salt, soy protein, vegetable protein, milk protein, egg white, aromas, flavor
enhancer (glutamate monosodium), stabilizer (xanthan gum), acidity (lactic
acid), cephalopod ink, (mollusc), natural extracts (garlic and chilli). May contain
traces of crustacea.
ND
SUR-10 Big
distribution
(Spain)
Spain Surimi sticks–seafood
flavour
Surimi (Fish), water, sunflower oil, cephalopod (mollusc), starch and modified
starch, salt, egg white, vegetable protein, flavorings (contain crustaceans),
flavor enhancer (monosodium glutamate), sugar, natural colorings (cochineal
and paprika extract)
ND
SUR-11 Big
distribution
(Spain)
Spain Surimi product Surimi (Fish), water, sunflower oil, wheat flour, cephalopod (mollusc), salt,
soy protein, vegetable protein, milk protein, egg albumen, aromas, flavor
enhancer (E621), stabilizer (E415), acidity regulator (E270), cephalopod ink
(mollusc)
ND
SUR-12 Big
distribution
(Spain)
Spain Surimi in brine–crab flavour White fish, squid, sugar, sorbitol (E420), polyphosphates (E452), water,
potato starch, crabmeat (4%), vegetable oil, egg, salt, flavoring crab, flavor
enhancers (E621, E635), stabilizer (carrageenan), colorants (E171, E120,
E160c). Pickle ingredients: water, salt, citric acid, trisodium citrate, sodium
benzoate, tartaric acid
ND
SUR-13 Small
retailers
(Italy)
Korea Lobster tails imitation Alaska pollock (55,78%), water, wheat starch, egg white, lobster extract, rice
alcohol, salt, sugar, soybean oil, natural coloring: paprika
Gadus
chalcogrammus
SUR-14 Small
retailers
(Italy)
Lithuania Surimi sticks–crab flavour Surimi (38%), water, starch, egg white, rapeseed oil, soy proteins, salt, sugar,
tapioca starch and acetylated potato, crab aroma, whole egg, E621, E631,
E635, E160, E120
ND
SUR-15 BIP
(Italy)
China Surimi sticks–crab flavour Surimi 44%, wheat starch, soybean oil, crab flavor, crab extract, egg white,
potato flour
Nemipterus sp.
SUR-16 BIP
(Italy)
Thailand Fish-shaped crab meat
imitation
Surimi 35%, palm oil, modified tapioca starch, egg white, soy protein, crab
extract.
Nemipterus sp.
IC: Internal code BIP: Border Inspection Post
https://doi.org/10.1371/journal.pone.0185586.t001
Species identification in surimi-based products using Next Generation Sequencing technologies
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Preparation of barcoded libraries
A specific barcoded library was prepared for the amplicon obtained from each SBPs using the
Ion Plus Fragment Library Kit (Thermo Fisher Scientific) (IPFL kit), that allowed amplicons’
end-repair and ligation to Ion-compatible adapters.
Amplicons end-repair and purification. 20 ng of each amplified sample were diluted in a
total volume of 79 μl of nuclease-free water (Life Technologies). Amplicons’ end-repair was
done by adding 20 μl of 5X End Repair Buffer and 1 μl of End Repair Enzyme (both provided
by the IPFL kit) and incubating the reaction at room temperature for 20 minutes. The samples
were then purified with Agencourt1 AMPure1 XP Kit for DNA purification (Beckman Coul-
ter, Beverly, Massachusetts, USA) on a DynaMag™-2 magnet magnetic rack (Thermo Fisher
Scientific) following the procedure proposed by the manufacturer.
Adaptors ligation, nick reparation and purification of the amplicons. Adaptors pro-
vided in the Ion Xpress™ Barcode Adapters 1–16 (Thermo Fisher Scientific) were used. The
same Ion Xpress™ P1 Adapter was ligated to the amplicons obtained from all the SBPs samples
whereas a unique Ion Xpress™ Barcode Adapter for each sample was used. Adaptors ligation
and nick repair phases were done in a final reaction volume of 100 μl, containing: 25 μl of end-
repaired and purified amplicon with 10 μl of 10X Ligase Buffer, 2 μl of dNTP Mix, 2 μl of DNA
ligase and 8 μl of Nick Repair Polymerase (all provided by the IPFL kit), 2 μl of Ion P1 Adapter,
2 μl of Ion Xpress™ Barcode Adapter, 49 μl of nuclease-free water (Life Technologies). Each
reaction mix tube was run on an Applied Biosystems Veriti™ 96 well Thermal Cycler (Thermo
Fisher Scientific) with the program proposed by the IPFL kit manufacturer. The samples were
then purified with Agencourt1 AMPure1 XP Kit for DNA purification (Beckman Coulter,
Beverly, Massachusetts, USA) on a DynaMag™-2 magnet magnetic rack (Thermo Fisher Scien-
tific) following the procedure proposed by the manufacturer. Purified products were quanti-
fied by an Agilent 2100 Bioanalyzer (Agilent Genomics).
Libraries amplification and quantification. Libraries were amplified on an Applied
Biosystems Veriti™ 96 well Thermal Cycler (Thermo Fisher Scientific) in a total reaction vol-
ume of 130 μl, containing 100 μl of Platinum1PCR SuperMix High Fidelity, 5 μl of Library
Amplification Primer Mix (both provided by the IPFL kit) and 25 μl of unamplified library.
The cycling program suggested on the IPFL kit protocol was applied. Amplified libraries were
purified with Agencourt1 AMPure1 XP Kit for DNA purification (Beckman Coulter, Beverly,
Massachusetts, USA) on a DynaMag™-2 magnet magnetic rack (Thermo Fisher Scientific)
following the procedure proposed by the manufacturer. Agilent 2100 Bioanalyzer (Agilent
Genomics) was used to determine the molar concentration of each barcoded library. Three
equimolar pools of barcoded libraries were prepared: barcoded libraries from SUR-1 to SUR-6
(Pool 1), from SUR-7 to SUR-12 (Pool 2) and from SUR-13 to SUR-16 (Pool 3) were pooled
together. The three pools were quantified on Agilent 2100 Bioanalyzer (Agilent Genomics) or
Library TaqManTM Quantitation Kit (Thermo Fisher Scientific) following the procedure pro-
posed by the manufacturer, and then diluted as proposed by the Ion PGM™ Hi-Q™ Chef Kit
(Thermo Fisher Scientific).
Massive DNA clonal parallel amplification and sequencing by synthesis
Ion Sphere™ Particles (ISP) preparation and chips loading. The Ion PGM™ Hi-Q™ Chef
Kit (Thermo Fisher Scientific) was utilized to prepare template-positive Ion Sphere™ Particles
(ISP) and to load three Ion 314™ v2 BC sequencing chips (Chip 1 for Pool 1, Chip 2 for Pool 2
and Chip 3 for Pool 3) on Ion Chef™ System (Thermo Fisher Scientific) following the manufac-
turer protocol.
Species identification in surimi-based products using Next Generation Sequencing technologies
PLOS ONE | https://doi.org/10.1371/journal.pone.0185586 October 2, 2017 5 / 18
Sequencing by synthesis. The three chips sequencing was done on an Ion PGM™System
(Thermo Fisher Scientific) using the Ion PGM™ Hi-Q™ Sequencing Kit (Thermo Fisher Scien-
tific) according to the manufacturer protocol. Reads obtained from the three sequencing chips
were processed by the software Torrent Suite™ version 5.0 (Thermo Fisher Scientific).
Bioinformatics analysis
Data quality assessment. Each sequencing chip was primarily overall evaluated with the
Torrent Suite™ version 5.0 (Thermo Fisher Scientific) software on the basis of the final number
of usable reads (overall quality assessment) and of the reads length. Regarding the overall qual-
ity, we considered as acceptable a ISP loading higher than 70%, jointly with a polyclonal
amount lower than 20% and a final percentage of usable library higher than 80% (weak pres-
ence of low quality reads). The reads length was considered as cornerstone of a good sequenc-
ing outcome if the distribution of the major part of the reads (expressed as a graphic peak)
corresponded to the length of the target amplicon. Then, the FASTQ files for each barcoded
sample (that contain the raw sequences and their quality values) were downloaded from the
software and analysed through the program FastQC High Throughput Sequence QC Report
version 0.11.5 (www.bioinformatics.babraham.ac.uk/projects/). We put attention to the total
number of the raw reads and to their length (both provided by the FastQC program), that
might be long enough to include the target amplicon.
Reads taxonomic assignment and analysis of frequencies. The raw FASTQ files were
sent to Era7 Bioinformatics (Cambridge MA, USA) for obtaining their taxonomic profile. In
details, according to the final report providing from Era7, the sequences were filtered on the
basis of a minimum length of 100 bp and a maximum of ~300 bp (to contain the target ampli-
con). The sequences were also filtered on the basis of their quality in order to ensure a highly
supported taxonomic assignment. Filtered reads were then assigned to a taxonomic tree node
based on sequence similarity to 16SrRNA genes included in Era7 internal database, built with
16S sequences extracted from from RNAcentral database (http://rnacentral.org/). RNAcentral
database includes rRNAs from a wide set of important databases as SILVA, GreenGenes, RDP,
RefSeq and ENA. The NCBI taxonomy was used and for taxonomic assignment the MG7
method, that is based on a BLAST comparison of each read against the 16S ribosomal RNA
database, was applied. Samples’ species identification was based on the BLAST results. In par-
ticular, taxonomic assignment was done using 2 different algorithms: (i) Best BLAST Hit
(BBH) assignment, obtained by the BLASTN of each read against the internal 16S database
(each read was assigned to the taxon corresponding to the Best Blast Hit over a threshold of
similarity) and (ii) Lowest Common Ancestor (LCA) assignment, where each read was
assigned to the most probable taxon where it could come from. The frequencies for each tax-
onomy node were also assessed. Phylum, Family, Genus and species distribution in all the
samples was assessed. The frequencies were expressed in % with respect to the total merged
reads of each sample. Moreover, BBH assignments were used to calculate the diversity index
for each sample. In particular, Simpson’s diversity index was applied.
SBPs mislabelling assessing
A preliminary analysis of the information reported on the label was performed in the light of
the current European legislation [9,10] and coupled with the analytical results to evaluate the
mislabelling degree of the SBPs. In particular, we used the following criteria to consider one
case of mislabelling:: (A) labels did not report the precise term “fish” among the ingredients
(B) labels did not report the precise term “molluscs” among the ingredients (whereas
declared); (C) among the labels voluntarily reporting the scientific name, those in which the
Species identification in surimi-based products using Next Generation Sequencing technologies
PLOS ONE | https://doi.org/10.1371/journal.pone.0185586 October 2, 2017 6 / 18
declared species did not correspond to the ones retrieved by the analysis; (D) labels did not
declare the presence of molluscs but the analysis proved the presence of species belonging to
this Phylum.
Results and discussion
Samples collection
The traditional SBPs trade, based on Chinese exports to Europe, has recently slowed down
since Europe has increased its own SBPs manufacturing activity. Spain plays an important role
in the European surimi sector, being one of the most important producer and consumer of
SBPs, jointly with France [4]. Apart from the two SBPs collected at the BIP (SUR-15 and SUR-
16), produced in China and Thailand respectively, the fourteen samples directly purchased in
this study in Spain and Italy were produced in European countries, except for one (SUR-13)
which was produced in Korea and purchased at an Italian small retailer. Twelve samples
reported on the label the presence of “fish” in the list of ingredients, sometimes adding an
adjective or a noun such as “white fish”, “fish pulp” or “fish protein”. The scientific name of
the utilized species was reported in four samples and corresponded to Micromesistius poutas-sou (SUR-6), Gadus chalcogrammus (SUR-13) and Nemipterus spp. (SUR-15 and SUR-16).
Ten samples reported the presence of “molluscs”, either among the main ingredients or as
aroma/extract, or both. The percentage of surimi paste was also reported in seven samples. In
all the SBPs miscellaneous ingredients were also listed, such as wheat starch, potato, salt, soy-
bean oil and sugar (Table 1).
Primers selection
Since the maximum target read length of Ion PGM sequencing system is 400 bp, the amplicon
selected as target must be shorter. The primer pair used in this study, already tested in a previ-
ous study [20], was proved able to amplify a fragment of ~250–260 bp (depending on the
species) from fish as well as a fragment of ~190–200 bp (depending on the species) from ceph-
alopod species. Therefore, it can be successfully used for the amplification of extremely pro-
cessed products such as surimi, where a high degree of DNA degradation is known [7]. In
addition, although they have been originally designed to amplify only cephalopod species [20],
a recent study [21] has shown their capability in amplifying DNA from more than eighty spe-
cies of fish and cephalopods.
High Throughput Sequencing and data analysis
Overall quality control of the reads. Modern high throughput sequencers can generate
tens of millions of sequences in a single run. Therefore, preliminary suitable quality control
checks of the raw data are required before approaching subsequent analysis.
Overall, 674.983 raw sequences (78% of total analysed) and 674.826 raw sequences (73% of
total analysed) were obtained from Chip 1 and Chip 2, respectively. The sequences were con-
sidered as “usable” since they respected the threshold values established in materials and meth-
ods section (see paragraph “Data quality assessment”). Moreover, the global distribution peak
of the reads corresponded to the length of the target amplicon. Chip 3 was less performant as
the 668.081 raw sequences evaluated as usable represented only 58% of all the sequences ana-
lysed. Moreover, the polyclonal percentage (32%) was higher than the threshold value. How-
ever, since the final usable library was good (85%), few low-quality sequences were present
(14%) and the read lengths corresponded to the expected length of the target amplicons, these
data were considered as usable for subsequent bioinformatics analysis.
Species identification in surimi-based products using Next Generation Sequencing technologies
PLOS ONE | https://doi.org/10.1371/journal.pone.0185586 October 2, 2017 7 / 18
FastQC analysis. Comparison between FastQC analysis of raw and filtered reads per each
sample was reported in Table 2. Raw reads considered suitable in term of quality by Torrent
Suite™ version 5.0 software (Thermo Fisher Scientific) ranked between 2431 and 259531 and
their length ranked between a minimum of 25 bp to a maximum of 354 bp. Filtration phase
reduced the number of reads by selecting a minimum length of 100 bp, while the maximum
length was between 262 bp and 321 bp. This step allowed to preserve the two target amplicons
(250–260 bp for fish and 190–200 for cephalopods) and easing the taxonomic analysis by
removing too short fragments that could have given uncertain results. After the filtration step,
the total number of usable reads was not much lower than that of raw reads, with a preserva-
tion ranging from 75.3% to 88.2%, in the case of Chip 1 and Chip 2. On the contrary, final
usable reads of Chip 3 were lower, with a preservation ranging from 37.8% to 51.1%, confirm-
ing the worse outputs obtained in the previous overall reads analysis.
Reads taxonomic assignment, analysis of frequencies and samples diversity index.
Phylum distribution (cumulative % LCA) in the samples is shown in Fig 1. Even though, as
Table 2. Comparison between FastQC analysis of raw and filtered reads obtained from each sample.
Sample Raw reads Filtered reads Preserved reads (%)
Number Length (bp) Number Length (bp)
SUR-1 21597 25–333 19056 100–313 88.2
SUR-2 79174 25–332 68051 100–299 86
SUR-3 69682 25–292 59820 100–278 85.8
SUR-4 154476 25–325 126906 100–310 82.2
SUR-5 184772 25–346 155618 100–294 84.2
SUR-6 106418 25–354 91054 100–311 85.6
SUR-7 68584 25–312 53647 100–290 78.2
SUR-8 2431 25–262 1831 100–262 75.3
SUR-9 72162 25–318 59494 100–292 82.4
SUR-10 82491 25–321 64473 100–321 78.1
SUR-11 259531 25–319 207017 100–302 79.8
SUR-12 115899 25–339 96113 100–299 82.9
SUR-13 54134 25–307 23853 100–277 44.1
SUR-14 54572 25–297 28104 100–292 51.5
SUR-15 38203 25–296 17976 100–293 47.1
SUR-16 57674 25–316 21815 100–300 37.8
https://doi.org/10.1371/journal.pone.0185586.t002
Fig 1. Phylum distribution (cumulative % LCA) in each analysed SBP.
https://doi.org/10.1371/journal.pone.0185586.g001
Species identification in surimi-based products using Next Generation Sequencing technologies
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predictable, the Phylum Cordata was the most represented in all the SBPs (always greater than
75% and in 75% of the samples greater than 90%), the Phylum Mollusca was also found in
100% of the samples, in different percentages. In particular, 25% of the samples contained less
than 1% of molluscs’ DNA, 50% between 1% and 10%, 12.5% between 10% and 20%, and
12.5% more than 20%. Regardless of the quantities of DNA found in the samples, these results
substantially confirmed that the use of molluscs in surimi products is very common in the sea-
food industry. Literature reported in fact the high resistance to freeze-induced denaturation
and to proteolytic attack of cephalopods myofibrillar proteins [2], as well as the fact that even a
small amount of these proteins considerably improves the texture of a gel product, making it
more elastic and with a greater cohesiveness [23].
Results of the family, genus and species distribution in all the samples were reported in
Table 3. Given the great amount of assigned reads, only taxonomical entities present in the
samples in amount >1% were reported. Overall, DNA from 13 families, 19 genera and 16 spe-
cies of fish, and from 3 families, 3 genera and 3 species of cephalopods was found in SBPs. Figs
2 and 3 depict the distribution of families and genera in the samples. Regarding fish, although
some differences in composition between EU and Asian SBPs subsisted, DNA belonging to
the Gadidae family was found in 100% of the samples. The percentage was rather high in most
of the cases, exceeding 90% in 50% of the samples, ranging from 70 to 90% in 31.2% of the
samples and from 40 to 70% in 12.5% of the samples. Gadidae were poorly represented (<2%)
only in one Asian sample (SUR-13). DNA from Gadus genus was found in 100% of the sam-
ples, with the species Gadus chalcogrammus identified in 93.75% of the samples, whereas DNA
from Gadus morhua was detected in two samples. Also, DNA from Arctogadus genus/Arctoga-dus glacialis species, Melanogrammus genus/Melanogrammus aeglefinus species and Merlan-gius genus/Merlangius merlangus species was detected in 6.25%, 43.75% and 6.25% of the
samples, respectively. DNA belonging to Merluccidae family was found in 25% of the samples,
in variable percentages (from’ 1% to over 36%). and onlyMerluccius genus/Merluccius mer-luccius species was present in that samples. 12.3% of DNA from Nemipteridae family/Nemip-terus genus (species identification was not reached) was found only in SUR-4. Variable
percentage of DNA belonging to Carangidae (Trachurus spp.), Synodontidae (Saurida undos-quamis), Clupeidae (Dorosoma petenense and Ethmalosa fimabriata), Percidae (Sander spp.),
Engraulidae (Coilia grayii) Caesionidae (Pterocaesio tile), Siganidae (Siganus spp.), Lutjanidae
(Lutjanus bengalensis and Lutjanus rivulatus) and also to freshwater families such as Osphoro-
nemidae (Trichopodus leeri) and Cichlidae (Etroplus maculatus and Paretroplus maculatus) was
found in some samples. It is important to underline that in all the samples a variable percent-
age of DNA not identifiable at species level, but only at family or genus level, was present
(Table 3). These results substantially confirmed those already reported in literature. In fact, the
most part of the fish species found in the samples were those commonly used for surimi pro-
duction or sometimes reported in studies aimed at identifying species in such type of products.
Exceptions were represented by the non-EU samples SUR-13, SUR-15 and SUR-16 and by the
EU sample SUR-7, in which unconventionally species, never used until now, were found.
Regarding molluscs, it is primarily important to reiterate the fact that, although DNA from
molluscs was detected in all the samples, taxonomical assignment was reported in Table 3 only
if its presence was higher than 1%. DNA from Ommastrephidae family/Todarodes genus/
Todarodes pacificus species was found in 75% of the samples. DNA belonging to Loliginidae
family/Doryteuthis genus/ Doryteuthis opalescens species and Architeuthidae family/Archi-teuthis genus/Architeuthis dux species was also found in one sample (SUR-13). Differently
from fish, the molluscs species found in the analysed samples did not correspond to those
listed as the most used in surimi manufacture. In fact, the species T. pacificus, which was the
Species identification in surimi-based products using Next Generation Sequencing technologies
PLOS ONE | https://doi.org/10.1371/journal.pone.0185586 October 2, 2017 9 / 18
Table 3. Family, genus and species distribution in all the samples with relative percentages.
Sample Family Genus Species
SUR-1 Cordata Gadidae 91.2% Gadus 54.5% Merlangius 1.1% Gadus chalcogrammus 54.2% Gadidae 34.9%
Merlangius merlangus 1.1%
Mollusca Ommastrephidae 8.6% Todarodes 8.6% Todarodes pacificus 8.6%
SUR-2 Cordata Gadidae 85.1%Merluccidae 1.5% Gadus 57.1%Merluccius 1.1% Gadus chalcogrammus 56.9% Gadidae 27.0%
Merluccius merluccius 1.5%
Mollusca Ommastrephidae 12.5% Todarodes 12.5% Todarodes pacificus 12.5%
SUR-3 Cordata Gadidae 98.2% Gadus 63.5% Gadus chalcogrammus 63.20%Gadidae 33.6%
Mollusca Ommastrephidae 1.2% Todarodes 1.2% Todarodes pacificus 1.2%
SUR-4 Cordata Gadidae 75.0% Nemipteridae 12.3% Gadus 49.1% Nemipterus 12.3% Gadus morhua 25.5% Gadidae 25.0% Gadus
chalcogrammus 19.7% Nemipterus spp. 12.3%
Gadus spp. 3.8%
Mollusca Ommastrephidae 11.7% Todarodes 11.7% Todarodes pacificus 11.7%
SUR-5 Cordata Gadidae 42.9% Merluccidae 36.3% Merluccius 36.3% Gadus 28.9% Merluccius merluccius 36.3% Gadus chalcogrammus
28.8% Gadidae 13.5%
Mollusca Ommastrephidae 20.1% Todarodes 20.1% Todarodes pacificus 20.1%
SUR-6 Cordata Gadidae 99.3% Gadus 51.6% Arctogadus 2.7%
Melanogrammus 1.3%
Gadidae 43.2% Gadus morhua 41.9% Gadus spp.
9.1% Arctogadus glacialis 2.7% Melanogrammus
aeglefinus 1.3%
SUR-7 Cordata Gadidae 67.2% Cichlidae 10.7% Merluccidae
8.5% Percidae 1.3%
Gadus 36.9% Merluccius 8.6% Paretroplus
5.1% Etroplus 4.7% Sander 1.3%
Melanogrammus 1.1%
Gadus chalcogrammus 36.7% Gadidae 28.9%
Merluccius merluccius 8.5% Paretroplus maculatus
5.1% Etroplus maculatus 4.7% Sander spp. 1.3%
Melanogrammus aeglefinus 1.1%
Mollusca Ommastrephidae 7.9% Todarodes 7.9% Todarodes pacificus 7.9%
SUR-8 Cordata Gadidae 95.3% Gadus 53.1% Melanogrammus 1.5% Gadus chalcogrammus 52.4% Gadidae 39.7%
Melanogrammus aeglefinus 1.5%
Mollusca Ommastrephidae 3.9% Todarodes 3.9% Todarodes pacificus 3.9%
SUR-9 Cordata Gadidae 99.4% Gadus 57.1% Melanogrammus 2.7% Gadus chalcogrammus 56.7% Gadidae 39.3%
Melanogrammus aeglefinus 2.7%
SUR-10 Cordata Gadidae 94.4% Gadus 55.8% Melanogrammus 1.7% Gadus chalcogrammus 54.4% Gadidae 37.6%
Melanogrammus aeglefinus 1.7%
Mollusca Ommastrephidae 5.1% Todarodes 5.1% Todarodes pacificus 5.1%
SUR-11 Cordata Gadidae 99.4% Gadus 57.1% Melanogrammus 1.6% Gadus chalcogrammus 56.2% Gadidae 40.2%
Melanogrammus aeglefinus 1.6%
SUR-12 Cordata Gadidae 89.1% Merluccidae 2.7% Gadus 58.5% Merluccius 2.7%
Melanogrammus 1.4%
Gadus chalcogrammus 58.1% Gadidae 29.0%
Merluccius merluccius 2.7% Melanogrammus
aeglefinus 1.4%
Mollusca Ommastrephidae 7.4% Todarodes 7.4% Todarodes pacificus 7.4%
SUR-13 Cordata Synodontidae 19.9% Clupeidae 18.4% Percidae
9.1% Lutjanidae 7.1% Carangidae 4.6%
Osphoronemidae 2.7% Gadidae 1.6%
Scombridae 1.2% Engraulidae 1.1%
Saurida 19.9% Ethmalosa 13.6% Sander
8.8% Lutjanus 6.9% Trachurus 4.2%
Dorosoma 3.8% Trichopodus 2.6% Gadus
1.3% Coilia 1.1%
Saurida undosquamis 19.9% Ethmalosa fimbriata
13.6% Sander spp. 8.8% Percomorphaceae 4.8%
Trachurus spp. 4.2% Lutjanus spp. 4.1% Dorosoma
petenense 3.6% Lutjanus rivulatus 2.3% Trichopodus
spp. 1.3% Gadus chalcogrammus 1.3% Trichopodus
leeri 1.2% Coilia grayii 1.0%
Mollusca Architeuthidae 13.9% Loliginidae 6.9%
Ommastrephidae 1.5%
Architeuthis 13.9% Doryteuthis 6.9%
Todarodes 1.5%
Architeuthis dux 13.9% Doryteuthis opalescens 6.9%
Todarodes pacificus 1.5%
SUR-14 Cordata Gadidae 96.4% Gadus 66.9% Gadus chalcogrammus 66.3% Gadidae 28.2%
Mollusca Ommastrephidae 2.7% Todarodes 2.7% Todarodes pacificus 2.7%
SUR-15 Cordata Gadidae 85.8% Lutjanidae 3.5% Percidae 3.4% Gadus 57.7% Sander 2.9% Lutjanus 2.5%
Pterocaesio 1.0%
Gadus chalcogrammus 55.5% Gadidae 26.9%
Sander spp. 2.9% Gadus morhua 1.8% Lutjanus
bengalensis 1.1% Lutjanus rivulatus 1.0%
Pterocaesio tile 1.0%
Mollusca Ommastrephidae 2.8% Todarodes 2.8% Todarodes pacificus 2.8%
SUR-16 Cordata Gadidae 80.8% Lutjanidae 8.5% Gadus 51.7% Lutjanus 8.3% Siganus 1.8%
Scomber 1.0%
Gadus chalcogrammus 48.7% Gadidae 27.3%
Lutjanus bengalensis 5.8% Gadus morhua 2.4%
Lutjanus rivulatus 2.1% Siganus spp. 1.8%
https://doi.org/10.1371/journal.pone.0185586.t003
Species identification in surimi-based products using Next Generation Sequencing technologies
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most representative in this study, was very rarely reported, while the species A. dux was never
reported at all.
Diversity index was calculated to reflect how many different species there were in each sam-
ple. The obtained values of the Simpson’s diversity index (D Index) were reported and graphi-
cally illustrated in Fig 4. The most part of the samples (43.7%) presented a diversity index
between 0.5 and 0.6. The highest diversity index values (�0.8) were reached by the samples
SUR-4 and SUR-13, whereas the lowest (�0.5) by the samples SUR-3 and SUR-14. The diver-
sity index value did not seem to be directly correlated to the country origin of the sample.
SBPs’ label information: Mislabelling assessment
Mislabelling evaluation results were reported in Table 4. Overall, 37.5% of the SBPs’ were
found as mislabelled. Non-compliance involved 100% of SBPs produced in non-EU countries
and 23.1% of SBPs produced in EU countries. The final mislabelling percentage was: (i) 25% of
the samples did not report the exact term “fish”, but were simply labelled as “surimi” or, in the
Fig 2. Families presence and distribution in each sample. (E): SBP produced in Europe: (A): SBP produced in Asia.
https://doi.org/10.1371/journal.pone.0185586.g002
Species identification in surimi-based products using Next Generation Sequencing technologies
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case of SUR-13, only declared the commercial denomination of the species (“Alaska pollock”)
jointly with the scientific name (Gadus chalcogrammus). The use of the term “surimi” alone, as
well as the species declaration alone, are both non-compliant with the current Regulation since
it could be unclear, for the average consumer, that surimi is often produced from fish and mol-
luscs. The presence of allergens such as fish or mollusc should be clearly indicated in the label
since allergic consumers might not be aware of what they are really buying; (ii) 12,5% of the
samples reported an altered form of the term “molluscs”, indicating “shellfish” or “squid”,
which could be equally misleading and unclear for consumers; (iii) 25% of the samples volun-
tary declared a species that actually not corresponded to that found through the DNA analysis.
In SUR-6, where the presence of Micromesistius poutassou was declared, no DNA of this spe-
cies was found. On the contrary, the most part of DNA found in this sample belonged to the
species Gadus morhua or, in lower amount, Melanogrammus aeglefinus and Arctogadus glacia-lis. Species substitution also involved the Asian sample SUR-13, where the declared Gadus cal-chogrammus was actually a mixture of species mostly belonging to Synodontidae, Clupeidae
and Lutjanidae families, as well as SUR-15 and SUR-16, where the reported Nemipterus spp.
was not found at all; (iv) 25% of the samples (all produced in non-EU countries) not reported
Fig 3. Genus presence and distribution in each sample. (E): SBP produced in Europe: (A): SBP produced in Asia.
https://doi.org/10.1371/journal.pone.0185586.g003
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at all the presence of molluscs on the label, despite mollusc DNA was found through our
molecular analyses (Fig 1).
Mislabelling and health implications
In parallel with the global increase of seafood consumption, seafood allergy incidence has con-
siderably risen over the past 40 years. To date, fish is considered one of the eight most common
allergenic foods, collectively considered to be responsible for about 90% of food allergic reac-
tions [24]. Symptomatology can be severe and sometimes fatal. Fish meat is in fact one of the
foods most commonly responsible of severe anaphylaxis [25]. Parvalbumin, which is found in
all fish species, is reported to be the major fish allergen for 95% of patients suffering from IgE-
mediated fish allergy [26]. It is resistant to boiling and other high temperature processing, so
that adverse reactions can also occur after consuming fish in processed form. Moreover, many
other allergens have been recently characterised and identified. Noteworthy, there is evidence
that the allergenic power of different fish species may differ to some extent, with e.g. hake and
cod reportedly being among the more allergenic [24]. Molluscs hypersensitivity also represents
a very common food allergy type. Consumption of molluscs is assumed to be responsible of
reactions ranging from a mild oral allergy syndrome to severe symptoms such as anaphylactic
shock in sensitive consumers. Tropomyosin (TM) was the first allergen identified, but also in
this case other allergens have recently been characterized [27]. Allergy to surimi has been veri-
fied in a patient who reacted to 1 g of surimi [28]. According to the current food European reg-
ulation, labels must inform consumers on the allergic hazard of all seafood types [9]. To make
a clearer and standardized labelling system, in terms of allergenic seafood, the terms “fish” and
Fig 4. Simpson’s diversity index (D Index) values obtained for each sample.
https://doi.org/10.1371/journal.pone.0185586.g004
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“molluscs” must be reported. This obligation is absolutely opportune since the presence of fish
and molluscs, even in small percentage, could represent a hazard in allergic consumers. In fact,
current clinical, epidemiological and experimental data do not allow determining safe allergen
threshold levels that would not trigger adverse reactions in a sensitised consumer [24]. How-
ever, deficiencies in food labelling, particularly in products imported from Asian countries,
have been often ascertained [29]. Therefore, the mislabelling rate involving the SBPs produced
in Asian countries further confirmed the lower safety degree of these products, above all con-
sidering the absence of a standardized system for seafood labelling and traceability [30]. In this
study, samples not reporting the presence of “fish” and/or “molluscs” on the label actually rep-
resent an health hazard for allergic consumers. Noteworthy, another possible health hazard is
represented by the presence of the species L. rivulatus in two Asian samples, which has been
reported to be associated to ciguatera poisoning (fishbase.org).
Species composition of SBPs and evaluation of environmental impact
If the main large-scale source for surimi production is the Alaska pollock (Gadus chalcogram-mus), the variability of fish stocks and the limitation of this species around the world has led to
Table 4. SBPs mislabelling cases evaluated through both labels information analysis and sequences data results.
Sample Label information (ingredients) Label conformity
Fish Molluscs
SUR-1 fish - cephalopod (molluscs);
- flavour (containing shellfish)
correct
SUR-2 surimi (fish) - cephalopod (mollusc):
- containing cephalopod ink
correct
SUR-3 surimi (fish) cephalopod (mollusc) correct
SUR-4 surimi [fish and cephalopods (molluscs)] correct
SUR-5 surimi (fish) extract (molluscs) correct
SUR-6 surimi (fish pulp Micromesistius poutassou) Flavorings
(contains shellfish)
mislabelled
B; C
SUR-7 surimi (fish) cephalopod (molluscs) correct
SUR-8 surimi (fish) cephalopod (molluscs) correct
SUR-9 fish protein - cephalopod (molluscs);
- cephalopod ink (molluscs)
correct
SUR-10 surimi (fish) cephalopod (molluscs) correct
SUR-11 surimi (fish) - cephalopod (molluscs);
- cephalopod ink (molluscs)
correct
SUR-12 white fish Squid mislabelled
B
SUR-13 Alaska pollack Gadus chalchogrammus NR mislabelled
A; C; D
SUR-14 surimi NR mislabelled
A; D
SUR-15 surimi Nemipterus spp. NR mislabelled
A; C(*); D
SUR-16 surimi Nemipterus spp. NR mislabelled
A; C(*); D
NR: not reported; A: not reporting the precise term “fish” among the ingredients; B: not reporting the precise term “molluscs” among the ingredients
(whereas declared); C: the voluntarily declared species not correspond to that retrieved by the analysis; D: label not declare the presence of molluscs but
the analysis proved the presence of species belonging to this Phylum;(*): the declared species is present but in lower amount respect to other undeclared species.
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the exploitation of many other species, both among fish and cephalopods [2]. To date, more
than 80 species are in fact reported as a resource for surimi industry [21], belonging to a wide
and diverse taxonomic range. A recent study conducted by Galal-Khallaf et al. [5] has already
reported the use of a wide range of new species, sometimes vulnerable, in surimi production,
highlighting the necessity to proper identify species in such kind of foodstuff to better manage
overexploited and/or endangered marine resources. The results of our study further confirm
the presence of species traditionally used in surimi production, such as those belonging to the
groups of cods, haddocks and hakes. Alaska pollock (G. chalcogrammus), and in general spe-
cies included in the Gadus genus, was almost always found in both European and Asian SBPs.
Haddock (M. aeglefinus), already reported as commonly used, was in the same way often
found in European samples. On the contrary, to the best of our knowledge, whiting (M.mer-langus) and Arctic cod (A. glacialis) were not reported yet as a resource for surimi production.
As these two species were found in the samples produced in European countries, their pres-
ence could be explained by the fact that their habitat mostly includes the Northeast Atlantic
area, so that they are probably caught in European waters and then processed within the Com-
munity. The same occurs for the European hake (Merluccius merluccius), which has never
been reported in surimi production, while its congeners are worldwide exploited for this pur-
pose. On the contrary, Nemipterus spp., already reported as widely utilized in Asiatic products
[5], was found in the samples produced in the EU. Even though the identification at species
level was not reached, all Nemipteridae habit tropical and sub-tropical Indo-West Pacific
waters (fishbase.org). This implies that European surimi industry not only uses its own coun-
try resources, but also extra-EU species (which could be imported or directly caught in extra-
EU waters by European vessels). Moreover, since surimi can be processed from the flesh of
fish not only in land-based operations, but also on-board processing ships, it is not to consider
improbable that European ships operate in extra-EU waters, so that the products are conse-
quently composed by extra-EU resources.
Other species already reported in the literature were found in the analysed Asian samples,
such as Saurida undosquamis (Brushtooth lizardfish) and Trachurus spp. Noteworthy, the
presence of new unexpected species, generally characterized by low/not fishery interest, was
detected in both European and Asian samples. Among Clupeidae, Dorosoma petenense, a spe-
cies habiting North and Central America waters, and Ethmalosa fimbriata, from Eastern Cen-
tral Atlantic Ocean, were found in a sample produced in Korea, together with the Indo-Pacific
Coilia grayii (Engraulidae). Sander spp. (Percidae) was found in both European and Chinese
samples, but unfortunately the identification at species level was not reached, so that it was not
possible to attribute an origin to this fish. The Indo-Pacific Ptaerocaesio tile (Caesionidae) and
Siganus spp. (Siganidae) (which is commonly as used ornamental fish) were found in samples
produced in China and Thailand, respectively. Bengal snapper (Lutjanus bengalensis) and
Blupperlip snapper (Lutjanus rivulatus), habiting the Indian Ocean, were found in three Asian
samples. Finally, also freshwater fish were found: Etroplus maculatus, and Paretroplus macula-tus (Cichlidae), habiting Indian and African waters respectively, were found in a sample pro-
duced in Europe. P.maculatus, in particular, is reported as Critically Endangered (CE) species
by the IUCN Red List of Threatened Species (www.iucnredlist.org). Similarly, the freshwater
species Trichopodus leeri (Osphoronemidae), native of Malay Peninsula, Thailand and Indone-
sian waters, which was found in a Korean sample, is reported as Near Threatened (NT) by the
IUCN Red List of Threatened Species (www.iucnredlist.org). Among molluscs, whereas Dory-teuthis opalescens (Ommastrephidae) has already been reported for surimi production, to the
best of our knowledge no literature data concerning the use Todarodes pacificus (Ommastre-
phidae) and Architeuthis dux (Architeuthidae) have been reported yet.
Species identification in surimi-based products using Next Generation Sequencing technologies
PLOS ONE | https://doi.org/10.1371/journal.pone.0185586 October 2, 2017 15 / 18
Conclusions
In this work, the Ion Torrent NGS technology was tested for the first time on surimi-based
products. Although further studies aimed at optimizing and standardizing the analytical proto-
col, deepening the aspect of DNA quantification and obviously applying this technology to a
larger number of samples are required, the metabarcoding approach was proved to be suitable
for species identification of processed multispecies seafood products. Overall our results sug-
gest that surimi production is not related to a definite resource, but mostly depends to the
catching and processing area, fishing season and species availability. In particular, it seems that
in Asian region the overexploitation enforces the use of almost all of the catch for seafood
industry, often challenging the sustainable management and conservation of marine resources.
In fact, given the low percentage of DNA present in the SBPs for some species, it can be
excluded that these species are deliberately caught to be processed by the seafood industry but
rather they occasionally enter in the production chain. However, such a great and diversified
range of species, also including vulnerable and potentially toxic ones, as well as the often-unde-
clared presence of potentially allergic risks, strongly remarks the still too weak control system
and poorly eco-friendly management around the global seafood sector, highlighting the neces-
sity to further strengthen the tools aimed at ensuring both consumers and environmental
protection.
Acknowledgments
We thank Dr.ssa Lara Tinacci, FishLab, Department of Veterinary Sciences (University of
Pisa), for her help in collecting the samples.
Author Contributions
Conceptualization: Andrea Armani.
Data curation: Alice Giusti.
Formal analysis: Alice Giusti.
Funding acquisition: Carmen G. Sotelo.
Investigation: Alice Giusti.
Methodology: Carmen G. Sotelo.
Project administration: Carmen G. Sotelo.
Resources: Carmen G. Sotelo.
Software: Alice Giusti.
Supervision: Andrea Armani, Carmen G. Sotelo.
Writing – original draft: Alice Giusti, Andrea Armani.
Writing – review & editing: Andrea Armani, Carmen G. Sotelo.
References1. Brennan MA, Derbyshire E, Tiwari BK, Brennan CS. Ready-to-eat snack products: The role of extrusion
technology in developing consumer acceptable and nutritious snacks. Int. J. Food Sci. Tech. 2013, 48
(5):893–902.
2. Park JW. Surimi and surimi seafood. CRC Press 2013, third edition, 666 pp.
3. Ducept F, De Broucker T, Souliè JM, Trystram G, Cuvelier G. Influence of the mixing process on surimi
seafood paste properties and structure. J. Food Eng. 2012, 108(4), 557–562.
Species identification in surimi-based products using Next Generation Sequencing technologies
PLOS ONE | https://doi.org/10.1371/journal.pone.0185586 October 2, 2017 16 / 18
4. Vidal-Giraud B, Chateau D. (2007). World Surimi Market. GLOBEFISH Research Programme (FAO).
5. Galal-Khallaf A, Ardura A, Borrell YJ, Garcia-Vazquez E. Towards more sustainable surimi? PCR-clon-
ing approach for DNA barcoding reveals the use of species of low trophic level and aquaculture in Asian
surimi. Food Control 2016, 61:62–69.
6. Keskin E, Atar HH. Molecular identification of fish species from surimi-based products labeled as Alas-
kan pollock. J. Appl. Ichthyol. 2012, 28(5):811–814.
7. Pepe T, Trotta M, Di Marco I, Anastasio A, Bautista JM, Cortesi ML. Fish Species Identification in
Surimi-Based Products. J. Agr. Food Chem. 2007, 55(9):3681–3685.
8. Suarez DM, Manca E, Crupkin M, Paredi ME. Emulsifying and gelling properties of weakfish myofibrillar
proteins as affected by squid mantle myofibrillar proteins in a model system. Brazilian J. Food Technol.
2014, 17(1):8–18.
9. Regulation (EU) No 1169/2011 of the European Parliament and of the Council of 25 october 2011 on
the provision of food information to consumers, amending Regulations (EC) No 1924/2006 and (EC) No
1925/2006 of the European Parliament and of the Council, and repealing Commission Directive 87/250/
EEC, Council Directive 90/496/EEC, Commission Directive 1999/10/EC, Directive 2000/13/EC of the
European Parliament and of the Council, Commission Directives 2002/67/EC and 2008/5/EC and Com-
mission Regulation (EC) No 608/2004. OJ L 304, 22.11.2011, p. 18–63.
10. Regulation (EU) No 1379/2013 of the European Parliament and of the Council of 11 December 2013 on
the common organisation of the markets in fishery and aquaculture products, amending Council Regu-
lations (EC) No 1184/2006 and (EC) No 1224/2009 and repealing Council Regulation (EC) No 104/
2000. OJ L 354, 28.12.2013, p. 1–21.
11. D’Amico P, Armani A, Gianfaldoni D, Guidi A. New provisions for the labelling of fishery and aquaculture
products: Difficulties in the implementation of Regulation (EU) n. 1379/2013. Mar. Policy 2016, 71:147–
156.
12. Metzker ML. Sequencing technologies—the next generation. Nat. Rev. Genet. 2010, 11(1):31–46.
https://doi.org/10.1038/nrg2626 PMID: 19997069
13. Zaiko A, Martinez JL, Ardura A, Clusa L, Borrell YJ, Samuiloviene A, et al. Detecting nuisance species
using NGST: methodology shortcomings and possible application in ballast water monitoring. Mar.
Environ. Res. 2015, 112:64–72. https://doi.org/10.1016/j.marenvres.2015.07.002 PMID: 26174116
14. Bertolini F, Ghionda MC, D’Alessandro E, Geraci C, Chiofalo V, Fontanesi L. A next generation semi-
conductor based sequencing approach for the identification of meat species in DNA mixtures. PLoS
one 2015, 10(4):e0121701. https://doi.org/10.1371/journal.pone.0121701 PMID: 25923709
15. Tillmar AO, Dell’Amico B, Welander J, Holmlund G. A universal method for species identification of
mammals utilizing next generation sequencing for the analysis of DNA mixtures. PLoS one 2013, 8
(12):1–9.
16. Muñoz-Colmenero M, Martınez JL, Roca A, Garcia-Vazquez E. NGS tools for traceability in candies as
high processed food products: Ion Torrent PGM versus conventional PCR-cloning. Food Chem. 2017,
214:631–636. https://doi.org/10.1016/j.foodchem.2016.07.121 PMID: 27507519
17. Park JY, Lee SY, An CM, Kang JH, Kim JH, Chai JC, et al. Comparative study between Next Genera-
tion Sequencing Technique and identification of microarray for Species Identification within blended
food products. Biochip J. 2012, 6(4):354–361.
18. Carvalho DC, Palhares RM, Drummond MG, Gadanho M. Food metagenomics: Next generation
sequencing identifies species mixtures and mislabeling within highly processed cod products. Food
Control 2017, 80:183–186.
19. Kappel K, Haase I, Kappel C, Sotelo CG, Schroder U. Species identification in mixed tuna samples with
next-generation sequencing targeting two short cytochrome b gene fragments. Food Chem. 2017,
234:212–219. https://doi.org/10.1016/j.foodchem.2017.04.178 PMID: 28551228
20. Chapela MJ, Sotelo CG, Calo-Mata P, Perez-Martın RI, Rehbein H, Hold GL, et al. Identification of
Cephalopod Species (Ommastrephidae and Loliginidae) in Seafood Products by Forensically Informa-
tive Nucleotide Sequencing (FINS). J. Food Sci. 2002, 67(5):1672–1676.
21. Giusti A, Tinacci L, Sotelo CG, Marchetti M, Guidi A, Zheng W, et al. Seafood Identification in Multispe-
cies Products: Assessment of 16SrRNA, cytb, and COI Universal Primers’ Efficiency as a Preliminary
Analytical Step for Setting up Metabarcoding Next-Generation Sequencing Techniques. J. Agr. Food
Chem. 2017, 65(13):2902–2912.
22. Armani A, Tinacci L, Xiong X, Titarenko E, Guidi A, Castigliego L. Development of a Simple and Cost-
Effective Bead-Milling Method for DNA Extraction from Fish Muscles. Food Anal. Method. 2014, 7
(4):946–955.
23. Ehara T, Nakagawa K, Tamiya T, Noguchi SF, Tsuchiya T. Effect of paramyosin on invertebrate natural
actomyosin gel formation. Fisheries Sci. 2004, 70(2):306–313.
Species identification in surimi-based products using Next Generation Sequencing technologies
PLOS ONE | https://doi.org/10.1371/journal.pone.0185586 October 2, 2017 17 / 18
24. EFSA (2014). Scientific Opinion on the evaluation of allergenic foods and food ingredients for labelling
purposes. EFSA J., 12, 3894.
25. Lopata AL, Lehrer SB. New insights into seafood allergy. Curr. Opin. Allergy Cl. 2009, 9(3):270–277.
26. Swoboda I, Bugajska-Schretter A, Verdino P, Keller W, Sperr WR, Valent P., et al. Recombinant carp
parvalbumin, the major cross-reactive fish allergen: a tool for diagnosis and therapy of fish allergy. J.
Immunol. 2002, 168(9):4576–4584. PMID: 11971005
27. Pedrosa M, Boyano-Martınez T, Garcıa-Ara C, Quirce S. Shellfish allergy: a comprehensive review.
Clin. Rev. Allerg. Immu. 2015, 49(2):203–216.
28. Musmand JJ, Helbling A, Lehrer SB. Surimi: something fishy. J. Allergy Clin. Immun. 1996, 98(3):697–
699. PMID: 8828548
29. D’Amico P, Armani A, Castigliego L, Sheng G, Gianfaldoni D, Guidi A. Seafood traceability issues in
Chinese food business activities in the light of the european provisions. Food Control 2014, 35(1):7–13.
30. Xiong X, D’Amico P, Guardone L, Castigliego L, Guidi A, Gianfaldoni D, et al. The uncertainty of sea-
food labeling in China: A case study on Cod, Salmon and Tuna. Mar. Policy 2016, 68:123–135.
Species identification in surimi-based products using Next Generation Sequencing technologies
PLOS ONE | https://doi.org/10.1371/journal.pone.0185586 October 2, 2017 18 / 18